16,605 Data Scientists jobs in India

Data Scientists - Generative AI Specialist

Location - Noida

Experience - 4 to 5 years

Salary - 22 LPA

JOB DESCRIPTION :

* 3+ years experience in Data Science, focused on generative AI, agentic AI, LLMs, and NLP

* Hands-on with RAG pipelines, knowledge graphs, and prompt engineering

* Skilled in Azure AI tools: Azure OpenAI, Cognitive Services, and Azure ML

* Experience with LangChain, Agentic AI frameworks, and orchestration tools

* Proficient in Hugging Face for model building and fine-tuning

* Strong Python development skills for AI applications

* Worked with vector databases, embeddings, and semantic search implementations

* Solid MLOps background: CI/CD pipelines, DevOps integration, AI deployment optimization

* Familiar with FastAPI, Databricks, AWS, MLflow, Faiss, Redis, and OpenAI APIs

* Great problem-solver who enjoys debugging and improving AI systems

Intersted Candidates applies on or

Job Types: Full-time, Permanent

Pay: ₹2,200,000.00 per year

Benefits:

• Cell phone reimbursement
• Health insurance
• Paid sick time
• Paid time off
• Provident Fund

Work Location: In person

Were Hiring: Data Scientists Enterprise AI, ML & Advanced Analytics

(30+ Openings | 3-20 Yrs Exp | Multiple Levels)

Location: Mumbai / Pune / Chandigarh / Bengaluru / Gurugram / Noida / New Delhi / Kolkata / Hyderabad / Chennai (Remote and Hybrid options are available for some roles)

Industry: Fortune 500 Client Projects (Staffing via Hatchtra Innotech Pvt Ltd)

Employment Type: Full-Time | Contract (C2H)

About us:

Hatchtra is a leading staffing and workforce solutions company, trusted by Fortune 500 organizations and global enterprises to build their technology teams.

When you join us, you'll work directly with our Fortune 500 client teams that power mission-critical systems worldwide.

About the Role

We are seeking Data Scientists (3-20 years) to deliver advanced analytics, AI, and machine learning solutions for global enterprises. This role is perfect for professionals who thrive on solving complex business problems, building predictive models, and driving data-driven innovation at scale.

As part of world-class analytics teams, youll work on enterprise AI initiatives, ML model deployment, NLP, computer vision, and generative AI use cases to transform business outcomes.

Open Positions & Designations

• Associate Data Scientist / Junior ML Engineer (3–5 Yrs)
• Data Scientist / Senior Data Scientist (5–10 Yrs)
• Lead Data Scientist / AI Engineer (8–12 Yrs)
• Principal Data Scientist / AI Solutions Architect (10–15 Yrs)
• Director – Data Science & AI Strategy (15–20 Yrs)

Key Responsibilities (Scale with Level)

Professional (3–5 Yrs)

• Clean, preprocess, and analyze structured and unstructured data for model building.
• Build and evaluate ML models (classification, regression, clustering).
• Work with Python, R, and libraries like Scikit-learn, TensorFlow, PyTorch.
• Support data preparation, feature engineering, and exploratory data analysis (EDA).
• Create basic dashboards and visualizations to share findings with stakeholders.
• Collaborate with data engineers to productionize analytics pipelines.

Mid-Level (5–10 Yrs)

• Design and deploy end-to-end ML/AI solutions in enterprise environments.
• Develop deep learning models for NLP, computer vision, and recommendation systems.
• Integrate ML pipelines with cloud data platforms (AWS SageMaker, Azure ML, GCP Vertex AI).
• Implement MLOps best practices for model lifecycle management.
• Conduct advanced statistical modeling, A/B testing, and causal inference.
• Mentor junior team members and lead analytics initiatives.

Senior/Leadership (10–20 Yrs)

• Define and execute enterprise AI and data science strategy.
• Lead AI innovation programs (Generative AI, LLMs, reinforcement learning).
• Partner with executives to drive AI-driven digital transformation initiatives.
• Build and manage global data science teams and delivery frameworks.
• Ensure AI/ML governance, ethical AI compliance, and data privacy standards.
• Represent organization in AI/ML conferences, publications, and thought leadership.

Skills & Tools

• Core Skills: Machine Learning, Deep Learning, NLP, Predictive Modeling, AI Solutions
• Programming: Python, R, SQL, Java, Scala
• ML Frameworks: TensorFlow, PyTorch, Keras, Scikit-learn, Hugging Face Transformers
• Cloud AI Platforms: AWS SageMaker, Azure ML, GCP Vertex AI
• Big Data: Spark, Databricks, Snowflake, BigQuery, Redshift
• Visualization: Power BI, Tableau, Matplotlib, Seaborn
• MLOps Tools: MLflow, Kubeflow, Airflow, Docker, Kubernetes

• Preferred Certifications:

• Google Professional Machine Learning Engineer

• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate

Qualifications

• Bachelor's/Master's/PhD in Data Science, Computer Science, Statistics, Mathematics, or related field.
• 3+ years of experience in data science, AI, or advanced analytics roles.
• Proven expertise in building ML/DL models and deploying them in production.
• Experience with big data ecosystems and cloud AI platforms.
• For leadership roles: Strong experience in strategy, innovation, and global team management.

Why Join Us?

• Collaborate with Fortune 500 enterprises on AI-first transformation projects.
• Work on cutting-edge ML, deep learning, NLP, and generative AI initiatives.
• Exposure to global projects, certifications, and leadership opportunities.
• Competitive compensation, remote flexibility, and global career growth.

How to Apply

For quick consideration, please email your resume and include the desired position and experience level (e.g., "Data Engineer – Mid-Level") in the subject line.

Data scientists, BULK HIRE - TOP RATED MNC Completely Remote

PERMANENT HIRE

100% MNC CLIENT

100% WFH

MUST: 6 to 10 years YEARS EXPERIENCE AS data scientist

MAX 28L LPA

IMMEDIATE JOINERS ONLY

.IN /

Required Candidate profile

MUST: 6+ yrs as data scientist

Strong exp in python, R Language, power bi, Gnn AI and LLM is a plus

Background verification Mandatory PF Mandatory

.IN /

Data Scientist Python and Notebooks

Responsibilities

Job Description We are seeking a talented Data Scientist to join our team and drive datadriven decisionmaking across our organization The ideal candidate will have a strong background in statistical analysis machine learning and data visualization with experience working with large datasets in a Teradata environment

Responsibilities

Design and implement endtoend data science projects from problem definition to model deployment

Develop and apply advanced machine learning algorithms and statistical models to solve complex business problems

Collaborate with crossfunctional teams to identify opportunities for datadriven improvements

Conduct exploratory data analysis and feature engineering to prepare data for modeling

Create and maintain dashboards and reports to communicate insights to stakeholders

Optimize data collection procedures and ensure data quality

Stay current with the latest advancements in data science and machine learning techniques

Implement and maintain onpremise AIML solutions

Apply Explainable AI techniques to enhance model interpretability and transparency

Requirements

10-13 years of experience in data science or related field

Strong proficiency in Python R and SQL

Experience with Teradata and data lakelakehouse architectures

Expertise in machine learning algorithms statistical modeling and data visualization

Familiarity with big data technologies eg Hadoop Spark

Excellent problemsolving and communication skills

Experience with version control systems eg Git

Experience with onpremise AIML solutions

Knowledge of Explainable AI methods and their practical applications.

Location - Bengaluru,Hyderabad,Chennai,Pune

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Requirements

• Frontend Framework: Angular

• ervers : Tomcat, Jetty, JBoss, Nginx, Apache HTTP Server

• T ols : Maven, Log4j 2, JUnit 5, Mockito, Postman, Swagger,

JMeter, Logback

• O : Windows, Linux

• V rsion Control : Git, GitHub

• I E : Eclipse, STS, IntelliJ IDEA

• M ssaging Systems : Apache Kafka

• C oud : AWS, Azure

• D vOps Tools : Docker, Kubernetes, GitLab

• F ontend Framework: Angular

• S rvers : Tomcat, Jetty, JBoss, Nginx, Apache HTTP Server

• T ols : Maven, Log4j 2, JUnit 5, Mockito, Postman, Swagger,

JMeter, Logback

• O : Windows, Linux

• V rsion Control : Git, GitHub

• I E : Eclipse, STS, IntelliJ IDEA

• M ssaging Systems : Apache Kafka

• C oud : AWS, Azure

• D vOps Tools : Docker, Kubernetes, GitLab

Description

Key Responsibilities

AI/ML Development & Research

• Design, develop, and deploy advanced machine learning and deep learning models for complex business problems

• Implement and optimize Large Language Models (LLMs) and Generative AI solutions

• Build agentic AI systems with autonomous decision-making capabilities

• Conduct research on emerging AI technologies and their practical applications

• Perform model evaluation, validation, and continuous improvement

Cloud Infrastructure & Full-Stack Development

• Architect and implement scalable cloud-native ML/AI solutions on AWS, Azure, or GCP

• Develop full-stack applications integrating AI models with modern web technologies

• Build and maintain ML pipelines using cloud services (SageMaker, ML Engine, etc.)

• Implement CI/CD pipelines for ML model deployment and monitoring

• Design and optimize cloud infrastructure for high-performance computing workloads

Data Engineering & Database Management

• Design and implement data pipelines for large-scale data processing

• Work with both SQL and NoSQL databases (PostgreSQL, MongoDB, Cassandra, etc.)

• Optimize database performance for ML workloads and real-time applications

• Implement data governance and quality assurance frameworks

• Handle streaming data processing and real-time analytics

Leadership & Collaboration

• Mentor junior data scientists and guide technical decision-making

• Collaborate with cross-functional teams including product, engineering, and business stakeholders

• Present findings and recommendations to technical and non-technical audiences

• Lead proof-of-concept projects and innovation initiatives

Required Qualifications

Education & Experience

• Master's or PhD in Computer Science, Data Science, Statistics, Mathematics, or related field

• 5+ years of hands-on experience in data science and machine learning

• 3+ years of experience with deep learning frameworks and neural networks

• 2+ years of experience with cloud platforms and full-stack development

Technical Skills - Core AI/ML

• Machine Learning: Scikit-learn, XGBoost, LightGBM, advanced ML algorithms

• Deep Learning: TensorFlow, PyTorch, Keras, CNN, RNN, LSTM, Transformers

• Large Language Models: GPT, BERT, T5, fine-tuning, prompt engineering

• Generative AI: Stable Diffusion, DALL-E, text-to-image, text generation

• Agentic AI: Multi-agent systems, reinforcement learning, autonomous agents

Technical Skills - Development & Infrastructure

• Programming: Python (expert), R, Java/Scala, JavaScript/TypeScript

• Cloud Platforms: AWS (SageMaker, EC2, S3, Lambda), Azure ML, or Google Cloud AI

• Databases: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, Cassandra, DynamoDB)

• Full-Stack Development: React/Vue.js, Node.js, FastAPI, Flask, Docker, Kubernetes

• MLOps: MLflow, Kubeflow, Model versioning, A/B testing frameworks

• Big Data: Spark, Hadoop, Kafka, streaming data processing

Preferred Qualifications

• Experience with vector databases and embeddings (Pinecone, Weaviate, Chroma)

• Knowledge of LangChain, LlamaIndex, or similar LLM frameworks

• Experience with model compression and edge deployment

• Familiarity with distributed computing and parallel processing

• Experience with computer vision and NLP applications

• Knowledge of federated learning and privacy-preserving ML

• Experience with quantum machine learning

• Expertise in MLOps and production ML system design

Key Competencies

Technical Excellence

• Strong mathematical foundation in statistics, linear algebra, and optimization

• Ability to implement algorithms from research papers

• Experience with model interpretability and explainable AI

• Knowledge of ethical AI and bias detection/mitigation

Problem-Solving & Innovation

• Strong analytical and critical thinking skills

• Ability to translate business requirements into technical solutions

• Creative approach to solving complex, ambiguous problems

• Experience with rapid prototyping and experimentation

Communication & Leadership

• Excellent written and verbal communication skills

• Ability to explain complex technical concepts to diverse audiences

• Strong project management and organizational skills

• Experience mentoring and leading technical teams

Description

Key Responsibilities

AI/ML Development & Research

• Design, develop, and deploy advanced machine learning and deep learning models for complex business problems

• Implement and optimize Large Language Models (LLMs) and Generative AI solutions

• Build agentic AI systems with autonomous decision-making capabilities

• Conduct research on emerging AI technologies and their practical applications

• Perform model evaluation, validation, and continuous improvement

Cloud Infrastructure & Full-Stack Development

• Architect and implement scalable cloud-native ML/AI solutions on AWS, Azure, or GCP

• Develop full-stack applications integrating AI models with modern web technologies

• Build and maintain ML pipelines using cloud services (SageMaker, ML Engine, etc.)

• Implement CI/CD pipelines for ML model deployment and monitoring

• Design and optimize cloud infrastructure for high-performance computing workloads

Data Engineering & Database Management

• Design and implement data pipelines for large-scale data processing

• Work with both SQL and NoSQL databases (PostgreSQL, MongoDB, Cassandra, etc.)

• Optimize database performance for ML workloads and real-time applications

• Implement data governance and quality assurance frameworks

• Handle streaming data processing and real-time analytics

Leadership & Collaboration

• Mentor junior data scientists and guide technical decision-making

• Collaborate with cross-functional teams including product, engineering, and business stakeholders

• Present findings and recommendations to technical and non-technical audiences

• Lead proof-of-concept projects and innovation initiatives

Required Qualifications

Education & Experience

• Master's or PhD in Computer Science, Data Science, Statistics, Mathematics, or related field

• 5+ years of hands-on experience in data science and machine learning

• 3+ years of experience with deep learning frameworks and neural networks

• 2+ years of experience with cloud platforms and full-stack development

Technical Skills - Core AI/ML

• Machine Learning: Scikit-learn, XGBoost, LightGBM, advanced ML algorithms

• Deep Learning: TensorFlow, PyTorch, Keras, CNN, RNN, LSTM, Transformers

• Large Language Models: GPT, BERT, T5, fine-tuning, prompt engineering

• Generative AI: Stable Diffusion, DALL-E, text-to-image, text generation

• Agentic AI: Multi-agent systems, reinforcement learning, autonomous agents

Technical Skills - Development & Infrastructure

• Programming: Python (expert), R, Java/Scala, JavaScript/TypeScript

• Cloud Platforms: AWS (SageMaker, EC2, S3, Lambda), Azure ML, or Google Cloud AI

• Databases: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, Cassandra, DynamoDB)

• Full-Stack Development: React/Vue.js, Node.js, FastAPI, Flask, Docker, Kubernetes

• MLOps: MLflow, Kubeflow, Model versioning, A/B testing frameworks

• Big Data: Spark, Hadoop, Kafka, streaming data processing

Preferred Qualifications

• Experience with vector databases and embeddings (Pinecone, Weaviate, Chroma)

• Knowledge of LangChain, LlamaIndex, or similar LLM frameworks

• Experience with model compression and edge deployment

• Familiarity with distributed computing and parallel processing

• Experience with computer vision and NLP applications

• Knowledge of federated learning and privacy-preserving ML

• Experience with quantum machine learning

• Expertise in MLOps and production ML system design

Key Competencies

Technical Excellence

• Strong mathematical foundation in statistics, linear algebra, and optimization

• Ability to implement algorithms from research papers

• Experience with model interpretability and explainable AI

• Knowledge of ethical AI and bias detection/mitigation

Problem-Solving & Innovation

• Strong analytical and critical thinking skills

• Ability to translate business requirements into technical solutions

• Creative approach to solving complex, ambiguous problems

• Experience with rapid prototyping and experimentation

Communication & Leadership

• Excellent written and verbal communication skills

• Ability to explain complex technical concepts to diverse audiences

• Strong project management and organizational skills

• Experience mentoring and leading technical teams

Description

Key Responsibilities

AI/ML Development & Research

• Design, develop, and deploy advanced machine learning and deep learning models for complex business problems

• Implement and optimize Large Language Models (LLMs) and Generative AI solutions

• Build agentic AI systems with autonomous decision-making capabilities

• Conduct research on emerging AI technologies and their practical applications

• Perform model evaluation, validation, and continuous improvement

Cloud Infrastructure & Full-Stack Development

• Architect and implement scalable cloud-native ML/AI solutions on AWS, Azure, or GCP

• Develop full-stack applications integrating AI models with modern web technologies

• Build and maintain ML pipelines using cloud services (SageMaker, ML Engine, etc.)

• Implement CI/CD pipelines for ML model deployment and monitoring

• Design and optimize cloud infrastructure for high-performance computing workloads

Data Engineering & Database Management

• Design and implement data pipelines for large-scale data processing

• Work with both SQL and NoSQL databases (PostgreSQL, MongoDB, Cassandra, etc.)

• Optimize database performance for ML workloads and real-time applications

• Implement data governance and quality assurance frameworks

• Handle streaming data processing and real-time analytics

Leadership & Collaboration

• Mentor junior data scientists and guide technical decision-making

• Collaborate with cross-functional teams including product, engineering, and business stakeholders

• Present findings and recommendations to technical and non-technical audiences

• Lead proof-of-concept projects and innovation initiatives

Required Qualifications

Education & Experience

• Master's or PhD in Computer Science, Data Science, Statistics, Mathematics, or related field

• 5+ years of hands-on experience in data science and machine learning

• 3+ years of experience with deep learning frameworks and neural networks

• 2+ years of experience with cloud platforms and full-stack development

Technical Skills - Core AI/ML

• Machine Learning: Scikit-learn, XGBoost, LightGBM, advanced ML algorithms

• Deep Learning: TensorFlow, PyTorch, Keras, CNN, RNN, LSTM, Transformers

• Large Language Models: GPT, BERT, T5, fine-tuning, prompt engineering

• Generative AI: Stable Diffusion, DALL-E, text-to-image, text generation

• Agentic AI: Multi-agent systems, reinforcement learning, autonomous agents

Technical Skills - Development & Infrastructure

• Programming: Python (expert), R, Java/Scala, JavaScript/TypeScript

• Cloud Platforms: AWS (SageMaker, EC2, S3, Lambda), Azure ML, or Google Cloud AI

• Databases: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, Cassandra, DynamoDB)

• Full-Stack Development: React/Vue.js, Node.js, FastAPI, Flask, Docker, Kubernetes

• MLOps: MLflow, Kubeflow, Model versioning, A/B testing frameworks

• Big Data: Spark, Hadoop, Kafka, streaming data processing

Preferred Qualifications

• Experience with vector databases and embeddings (Pinecone, Weaviate, Chroma)

• Knowledge of LangChain, LlamaIndex, or similar LLM frameworks

• Experience with model compression and edge deployment

• Familiarity with distributed computing and parallel processing

• Experience with computer vision and NLP applications

• Knowledge of federated learning and privacy-preserving ML

• Experience with quantum machine learning

• Expertise in MLOps and production ML system design

Key Competencies

Technical Excellence

• Strong mathematical foundation in statistics, linear algebra, and optimization

• Ability to implement algorithms from research papers

• Experience with model interpretability and explainable AI

• Knowledge of ethical AI and bias detection/mitigation

Problem-Solving & Innovation

• Strong analytical and critical thinking skills

• Ability to translate business requirements into technical solutions

• Creative approach to solving complex, ambiguous problems

• Experience with rapid prototyping and experimentation

Communication & Leadership

• Excellent written and verbal communication skills

• Ability to explain complex technical concepts to diverse audiences

• Strong project management and organizational skills

• Experience mentoring and leading technical teams

Description

Key Responsibilities

AI/ML Development & Research

• Design, develop, and deploy advanced machine learning and deep learning models for complex business problems

• Implement and optimize Large Language Models (LLMs) and Generative AI solutions

• Build agentic AI systems with autonomous decision-making capabilities

• Conduct research on emerging AI technologies and their practical applications

• Perform model evaluation, validation, and continuous improvement

Cloud Infrastructure & Full-Stack Development

• Architect and implement scalable cloud-native ML/AI solutions on AWS, Azure, or GCP

• Develop full-stack applications integrating AI models with modern web technologies

• Build and maintain ML pipelines using cloud services (SageMaker, ML Engine, etc.)

• Implement CI/CD pipelines for ML model deployment and monitoring

• Design and optimize cloud infrastructure for high-performance computing workloads

Data Engineering & Database Management

• Design and implement data pipelines for large-scale data processing

• Work with both SQL and NoSQL databases (PostgreSQL, MongoDB, Cassandra, etc.)

• Optimize database performance for ML workloads and real-time applications

• Implement data governance and quality assurance frameworks

• Handle streaming data processing and real-time analytics

Leadership & Collaboration

• Mentor junior data scientists and guide technical decision-making

• Collaborate with cross-functional teams including product, engineering, and business stakeholders

• Present findings and recommendations to technical and non-technical audiences

• Lead proof-of-concept projects and innovation initiatives

Required Qualifications

Education & Experience

• Master's or PhD in Computer Science, Data Science, Statistics, Mathematics, or related field

• 5+ years of hands-on experience in data science and machine learning

• 3+ years of experience with deep learning frameworks and neural networks

• 2+ years of experience with cloud platforms and full-stack development

Technical Skills - Core AI/ML

• Machine Learning: Scikit-learn, XGBoost, LightGBM, advanced ML algorithms

• Deep Learning: TensorFlow, PyTorch, Keras, CNN, RNN, LSTM, Transformers

• Large Language Models: GPT, BERT, T5, fine-tuning, prompt engineering

• Generative AI: Stable Diffusion, DALL-E, text-to-image, text generation

• Agentic AI: Multi-agent systems, reinforcement learning, autonomous agents

Technical Skills - Development & Infrastructure

• Programming: Python (expert), R, Java/Scala, JavaScript/TypeScript

• Cloud Platforms: AWS (SageMaker, EC2, S3, Lambda), Azure ML, or Google Cloud AI

• Databases: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, Cassandra, DynamoDB)

• Full-Stack Development: React/Vue.js, Node.js, FastAPI, Flask, Docker, Kubernetes

• MLOps: MLflow, Kubeflow, Model versioning, A/B testing frameworks

• Big Data: Spark, Hadoop, Kafka, streaming data processing

Preferred Qualifications

• Experience with vector databases and embeddings (Pinecone, Weaviate, Chroma)

• Knowledge of LangChain, LlamaIndex, or similar LLM frameworks

• Experience with model compression and edge deployment

• Familiarity with distributed computing and parallel processing

• Experience with computer vision and NLP applications

• Knowledge of federated learning and privacy-preserving ML

• Experience with quantum machine learning

• Expertise in MLOps and production ML system design

Key Competencies

Technical Excellence

• Strong mathematical foundation in statistics, linear algebra, and optimization

• Ability to implement algorithms from research papers

• Experience with model interpretability and explainable AI

• Knowledge of ethical AI and bias detection/mitigation

Problem-Solving & Innovation

• Strong analytical and critical thinking skills

• Ability to translate business requirements into technical solutions

• Creative approach to solving complex, ambiguous problems

• Experience with rapid prototyping and experimentation

Communication & Leadership

• Excellent written and verbal communication skills

• Ability to explain complex technical concepts to diverse audiences

• Strong project management and organizational skills

• Experience mentoring and leading technical teams